IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1905.13508.html
   My bibliography  Save this paper

Clusters of investors around Initial Public Offering

Author

Listed:
  • Margarita Baltakien.e
  • Kk{e}stutis Baltakys
  • Juho Kanniainen
  • Dino Pedreschi
  • Fabrizio Lillo

Abstract

The complex networks approach has been gaining popularity in analysing investor behaviour and stock markets, but within this approach, initial public offerings (IPO) have barely been explored. We fill this gap in the literature by analysing investor clusters in the first two years after the IPO filing in the Helsinki Stock Exchange by using a statistically validated network method to infer investor links based on the co-occurrences of investors' trade timing for 69 IPO stocks. Our findings show that a rather large part of statistically similar network structures form in different securities and persist in time for mature and IPO companies. We also find evidence of institutional herding.

Suggested Citation

  • Margarita Baltakien.e & Kk{e}stutis Baltakys & Juho Kanniainen & Dino Pedreschi & Fabrizio Lillo, 2019. "Clusters of investors around Initial Public Offering," Papers 1905.13508, arXiv.org, revised Nov 2019.
    • Handle: RePEc:arx:papers:1905.13508
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1905.13508
    File Function: Latest version
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Piero Mazzarisi & Adele Ravagnani & Paola Deriu & Fabrizio Lillo & Francesca Medda & Antonio Russo, 2022. "A machine learning approach to support decision in insider trading detection," Papers 2212.05912, arXiv.org.
    2. Wojciech Wisniewski & Yuri Kalnishkan & David Lindsay & Si^an Lindsay, 2024. "Temporal distribution of clusters of investors and their application in prediction with expert advice," Papers 2406.19403, arXiv.org.
    3. Baltakienė, Margarita & Kanniainen, Juho & Baltakys, Kęstutis, 2021. "Identification of information networks in stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    4. Paola Deriu & Fabrizio Lillo & Piero Mazzarisi & Francesca Medda & Adele Ravagnani & Antonio Russo, 2022. "How Covid mobility restrictions modified the population of investors in Italian stock markets," Papers 2208.00181, arXiv.org.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1905.13508. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.